5 citations · 13 across the 5 of their papers we have counts for
7 papers · 1 filter
Can Zero-Shot Commercial APIs Deliver Regulatory-Grade Clinical Text DeIdentification?
Veysel Kocaman, Muhammed Santas, Yigit Gul +2
We evaluate the performance of four leading solutions for de-identification of unstructured medical text - Azure Health Data Services, AWS Comprehend Medical, OpenAI GPT-4o, and Jo…
Beyond Negation Detection: Comprehensive Assertion Detection Models for Clinical NLP
Veysel Kocaman, Yigit Gul, M. Aytug Kaya +4
Assertion status detection is a critical yet often overlooked component of clinical NLP, essential for accurately attributing extracted medical facts. Past studies have narrowly fo…
Understanding COVID-19 News Coverage using Medical NLP
Ali Emre Varol, Veysel Kocaman, Hasham Ul Haq +1
Being a global pandemic, the COVID-19 outbreak received global media attention. In this study, we analyze news publications from CNN and The Guardian - two of the world's most infl…
Mining Adverse Drug Reactions from Unstructured Mediums at Scale
Hasham Ul Haq, Veysel Kocaman, David Talby
Adverse drug reactions / events (ADR/ADE) have a major impact on patient health and health care costs. Detecting ADR's as early as possible and sharing them with regulators, pharma…
Spark NLP: Natural Language Understanding at Scale
Veysel Kocaman, David Talby
Spark NLP is a Natural Language Processing (NLP) library built on top of Apache Spark ML. It provides simple, performant and accurate NLP annotations for machine learning pipelines…
Improving Clinical Document Understanding on COVID-19 Research with Spark NLP
Veysel Kocaman, David Talby
Following the global COVID-19 pandemic, the number of scientific papers studying the virus has grown massively, leading to increased interest in automated literate review. We prese…